In the research and application of artificial intelligence, acquiring reliable and rich data has become a crucial part of developing high-efficient algorithm. In order to improve the accuracy and robustness of AI models, enterprises and researchers needs various datasets to train system to cope with complicated scenarios in real applications. This makes the progress of collecting and optimizing data crucial and directly affects the final performance of AI.

The robot is equipped with sensors for autonomous navigation, a 360-degree video feed to the control center, real-time sensing and analysis, and a dashboard where public officers can receive real-time information from and be able to monitor.

“The deployment of ground robots can replace our police officers for patrols to a large extent and help augment our surveillance and enforcement resources,” a Singapore officer said.

Seeing robots being used in Singapore is not uncommon. Last year, Singapore deployed Boston Dynamics’ four-legged droids, dubbed Spot, to its parks, garden, and nature reserves to remind people about social distancing.

At the beginning of 2016, Alibaba launched the ET City Brain for the task of refined urban management. Its first area was traffic management. In October 2017, Hangzhou City Brain “Tian Yao” was officially released. The transit time of the pilot area was reduced by 15.3%, and the time for ambulances to arrive at the scene was cut by 50%.

In recent years, with the continuous development and promotion of smart city, the number of smart city pilots in China has reached 290 according to the data released by the Ministry of Housing and Urban-Rural Development. Nexdata has developed multiple datasets, such as 16 Types — 12,500 Groups of Urban Refined Management Data, 2,000 People — Electric Bicycle Entering Elevator Data and 112 Kitchen Video Data, to empower the development of smart city.

16 Types — 12,500 Groups of Urban Refined Management Data

The data covers multiple scenarios (street, shop entrance, corridor, community entrance, construction site etc.) and different time periods. The accuracy of annotation is over 95%.

2,000 People — Electric Bicycle Entering Elevator Data

2,000 people participated in the data collection, each person 1 photo and 4 videos. The data includes multi-type elevators, multi-type electric bicycles, and multiple ages. The accuracy of annotation is over 97%.

112 Kitchen Video Data

Total video duration is nearly 100 hours. Data covers multiple scenarios and different time periods.

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Based on different application scenarios, developers needs customize data collection and annotation. For example, autonomous drive need fine-grained street view annotation, medical image analysis require super resolution professional image. With the integration of technology and reality, high-quality datasets will continue to play a vital role in the development of artificial intelligence.